405 citations · 499 across the 23 of their papers we have counts for
31 papers
MLC at HECKTOR 2022: The Effect and Importance of Training Data when Analyzing Cases of Head and Neck Tumors using Machine Learning
Vajira Thambawita, Andrea M. Storås, Steven A. Hicks +2
Head and neck cancers are the fifth most common cancer worldwide, and recently, analysis of Positron Emission Tomography (PET) and Computed Tomography (CT) images has been proposed…
Segmentation Consistency Training: Out-of-Distribution Generalization for Medical Image Segmentation
Birk Torpmann-Hagen, Vajira Thambawita, Kyrre Glette +2
Generalizability is seen as one of the major challenges in deep learning, in particular in the domain of medical imaging, where a change of hospital or in imaging routines can lead…
PolypConnect: Image inpainting for generating realistic gastrointestinal tract images with polyps
Jan Andre Fagereng, Vajira Thambawita, Andrea M. Storås +4
Early identification of a polyp in the lower gastrointestinal (GI) tract can lead to prevention of life-threatening colorectal cancer. Developing computer-aided diagnosis (CAD) sys…
Grid HTM: Hierarchical Temporal Memory for Anomaly Detection in Videos
Vladimir Monakhov, Vajira Thambawita, Pål Halvorsen +1
The interest for video anomaly detection systems has gained traction for the past few years. The current approaches use deep learning to perform anomaly detection in videos, but th…
Predicting tacrolimus exposure in kidney transplanted patients using machine learning
Andrea M. Storås, Anders Åsberg, Pål Halvorsen +2
Tacrolimus is one of the cornerstone immunosuppressive drugs in most transplantation centers worldwide following solid organ transplantation. Therapeutic drug monitoring of tacroli…
Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations
Steven Hicks, Andrea Storås, Michael Riegler +6
Deep learning has in recent years achieved immense success in all areas of computer vision and has the potential of assisting medical doctors in analyzing visual content for diseas…